Literature DB >> 25737479

MQAPsingle: A quasi single-model approach for estimation of the quality of individual protein structure models.

Marcin Pawlowski1, Lukasz Kozlowski2, Andrzej Kloczkowski1,3,4.   

Abstract

We present a Model Quality Assessment Program (MQAP), called MQAPsingle, for ranking and assessing the absolute global quality of single protein models. MQAPsingle is quasi single-model MQAP, a method that combines advantages of both "pure" single-model MQAPs and clustering MQAPs. This approach results in higher accuracy compared to the state-of-the-art single-model MQAPs. Notably, the prediction for a given model is the same regardless if this model is submitted to our server alone or together with other models. Proteins 2016; 84:1021-1028.
© 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Keywords:  CASP10; MQAP; model correctness; model quality assessment; protein prediction; protein structure; single-model MQAP

Mesh:

Substances:

Year:  2016        PMID: 25737479     DOI: 10.1002/prot.24787

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  7 in total

1.  Two New Heuristic Methods for Protein Model Quality Assessment.

Authors:  Wenbo Wang; Junlin Wang; Dong Xu; Yi Shang
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2018-11-09       Impact factor: 3.710

2.  Sorting protein decoys by machine-learning-to-rank.

Authors:  Xiaoyang Jing; Kai Wang; Ruqian Lu; Qiwen Dong
Journal:  Sci Rep       Date:  2016-08-17       Impact factor: 4.379

3.  MQAPRank: improved global protein model quality assessment by learning-to-rank.

Authors:  Xiaoyang Jing; Qiwen Dong
Journal:  BMC Bioinformatics       Date:  2017-05-25       Impact factor: 3.169

4.  PSICA: a fast and accurate web service for protein model quality analysis.

Authors:  Wenbo Wang; Zhaoyu Li; Junlin Wang; Dong Xu; Yi Shang
Journal:  Nucleic Acids Res       Date:  2019-07-02       Impact factor: 16.971

5.  Unsupervised and Supervised Learning over theEnergy Landscape for Protein Decoy Selection.

Authors:  Nasrin Akhter; Gopinath Chennupati; Kazi Lutful Kabir; Hristo Djidjev; Amarda Shehu
Journal:  Biomolecules       Date:  2019-10-14

6.  RFQAmodel: Random Forest Quality Assessment to identify a predicted protein structure in the correct fold.

Authors:  Clare E West; Saulo H P de Oliveira; Charlotte M Deane
Journal:  PLoS One       Date:  2019-10-21       Impact factor: 3.240

7.  Decoy selection for protein structure prediction via extreme gradient boosting and ranking.

Authors:  Nasrin Akhter; Gopinath Chennupati; Hristo Djidjev; Amarda Shehu
Journal:  BMC Bioinformatics       Date:  2020-12-09       Impact factor: 3.169

  7 in total

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